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DGDispatch
Tumour Microenvironment and Host Inflammatory Response Identified as Defining Features in Diffuse Large B-Cell Lymphoma: Presented at ICML
By Chris Berrie
LUGANO, SWITZERLAND -- June 14, 2005 -- Comprehensive molecular signatures from genetic expression profiling of tumours that share similar features identify tumour microenvironment and host inflammatory response as defining features in diffuse large B-cell lymphoma (DLBCL) and suggest rational treatment targets in these newly defined DLBCL subsets.
Use of genetic expression profiling in large B-cell lymphomas (LBCL) has to date followed two specific pathways -- comparisons of normal versus tumour cells and comparisons of tumours across different outcomes.
As a third approach, a study was designed "to see if we can identify subsets of tumours with specific features," said principal investigator Margaret A. Shipp, MD, director, Lymphoma Program, division of hematology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, Massachusetts, United States.
Dr. Shipp presented the findings of this study here on June 9th at the 9th International Conference on Malignant Lymphoma (ICML).
They used a new LBCL sample series of 210 newly diagnosed, previously untreated LBCL cases, 176 DLBCL cases, and 34 primary mediastinal LBCL (MLBCL) cases. Dr. Shipp stressed that last of these because primary MLBCL has a young female clinical setting as a localised disease with characteristic pathological features for which there is at present only empirical, partially effective treatments that have long-term toxicities.
Their first approach was to compare the genetic expression profiling of DLBCL versus MLBCL, which produced a robust differential signature for MLBCL that showed decreased B-cell antigen receptor (BCR) signalling pathway components, a distinctive cytokine pathway signature, and a very close signature similarity to that of classical Hodgkin's lymphoma.
The identification of a set of NFkB target genes provided a specific signature to differentiate between DLBCL and MLBCL.
The researchers then developed the analysis of the DLBCL substructure using a combination of 3 different clustering algorithms. These were clustered as the top 5% of genes with the highest reproducibility across duplicate samples and the largest variation between tumours.
They also used a resampling-based method, consensus clustering, that automatically selects the most stable number of clusters for each algorithm and uses a variety of multiple 200plus subsample iterations across 80% of the samples, to avoid skewing of the results by a small subset that might not be representative of a tumour.
Dr. Shipp explained this consensus clustering analysis, indicating how it arrived at the basis of the 3 robust consensus cluster signatures that were validated through an independent database analysis, which were the following:
- The "OxPhos" cluster, containing genes involved in oxidative phosphorylation, mitochondrial function, and electron transport, plus antiapoptotic BCL-2 family members and 26S proteasome components.
- The "BCR/Proliferation" cluster, containing cell cycle regulatory genes, DNA repair genes, BCR signalling components, and B-cell transcription factors.
- The "Host Response" (HR) cluster, containing T-cell receptor components, T/NK cell activation and complement cascade components, monocyte/macrophage and dendritic cell transcripts, antigen processing components and interferon-induced genes, tumour necrosis factor ligands/receptors, adhesion molecules, and extracellular matrix components.
As a brief illustration of the practicalities of this approach, Dr. Shipp considered the case of
T-cell/histocyte-rich LBCL (TC/HR-LBCL), which shows prominent T cell and histocyte infiltration with fewer DLBCL genetic abnormalities and increased incidence of advanced stage disease, splenectomy, and bone marrow involvement.
Dr. Shipp said the TC/HR-LBCL subtype falls into the HR cluster tumour type, and like TC/HR-LBCL, HR tumours show significance of presence in younger patients (P =.04) and higher incidence of splenic and bone marrow involvement (P =.02, P =.03, respectively).
Similarly, looking back to the DLBCL versus MLBCL comparisons, Dr Shipp illustrated how the MLBCL subset shows considerable overlap with the HR subset via its NFkB activation signature.
In emphasising the future scope of these new data, Dr Shipp said, "We are very interested in characterising the genetic basis for these identified substructures of large B-cell lymphoma, and we think that this can be done using the complementation of three different approaches. RNA-based expression profiling with the associated LBCL subtypes, a method called 'electronic-cytogenetics', and high-density [single nucleotide polymorphism] arrays."
Finally, there is now the need to use these substructures to identify selective rational therapeutic targets and to characterise selective target inhibitors using the molecular signatures of the response.
[Presentation title: Transcriptional Profiles of Large B-Cell Lymphomas: Molecular Heterogeneity and Rational Therapeutic Targets. Abstract 027]
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